Abhirup Ghosh

Mobile phones and personal wearable devices will play a major role in deploying public health screening and monitoring applications at scale, due to their pervasive penetration in the population and capability to sense the intricate details of daily lives. My research interest is to build machine learning algorithms and systems that are suitable for these applications and can run on the resource constrained end-devices. Alongside, I also care about the privacy of the users and want to protect individual’s data while enabling aggregate inferences. I use techniques from deep learning, computational geometry, algebraic topology, and statistics.

Currently, I am a Research Associate at the Mobile Systems Research Lab in the Department of Computer Science and Technology, University of Cambridge. I am working on the MEDEA project funded by the Wellcome Trust to detect Alzheimer’s disease using outdoor mobility and sleep data. I got my PhD in 2019 from the School of Informatics in the University of Edinburgh under Dr Rik Sarkar in “Machine Learning and Privacy Preserving Algorithms for Spatial and Temporal Sensing”. I was a Research Associate in the Department of Computing, Imperial College London under Dr Thomas Heinis (till 2020).

Homepage: https://abhirup-home.netlify.app/